Convolutional Neural Network: does each filter in each convolution layer create a new image?
About the images inside the CNN layers: I really recommend this article since there is no one short answer to this question and it probably will be better to experiment with it.

About the RGB input images: When needed to train on RGB pictures it is not advised to split the RGB channels, you can think of it by trying to identify a fictional cat with red ears, green body and blue tail. Each separated channel don't represent a cat, most certainly not with high confidence. I would recommend to transform you RGB images to gray scale and measure the network performance. If the performance are not sufficient you can make a 3D convolution layer. For example: If 30x30x3 is the input image, the filter has to be NxNx3.